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A decentralized defense model for covert zero-dynamic attacks in industrial control systems

Author

Listed:
  • Peng, Xiangzhen
  • Zheng, Chengliang
  • Shi, Jianyu
  • Cui, Xiaohui

Abstract

The architecture of Industrial Control Systems (ICS) has evolved into an integrated cyber-physical system, introducing covert, zero-dynamic cyberattack vectors that threaten the reliability of ICS. We address two issues: (1) how to use decentralized solutions to defend resource-constrained ICS against highly covert zero-dynamic attacks; (2) how to improve performance (meeting real-time, high-frequency interaction demands) while enhancing reliability via decentralization. We propose a defense model integrating blockchain, zero-knowledge proofs, and smart contract (SC) obfuscation to bolster ICS resilience. A customized zk-SNARK algorithm enables efficient identity authentication, completed in under 3 ms. The Garble framework obfuscates SCs, concealing ICS device IP addresses and disrupting attack chains. A blockchain acts as a secure intermediary between the engineer workstation (EW) and programmable logic controller (PLC). To reduce blockchain overhead, we refine a proportional–integral–derivative (PID)–based roulette wheel algorithm. Obfuscated SCs resist decompilation by tools such as Objdump, ensuring robust protection. Our node selection mechanism balances security and diversity, mitigating systemic biases like the Matthew effect. By leveraging blockchain to supply computational power for encrypting and protecting ICS data flows, we offer new insights into defending ICS against highly covert cyberattacks. Experimental evaluation validates the model’s effectiveness under real-world ICS scenarios.

Suggested Citation

  • Peng, Xiangzhen & Zheng, Chengliang & Shi, Jianyu & Cui, Xiaohui, 2026. "A decentralized defense model for covert zero-dynamic attacks in industrial control systems," Reliability Engineering and System Safety, Elsevier, vol. 265(PA).
    • Handle: RePEc:eee:reensy:v:265:y:2026:i:pa:s0951832025006830
    DOI: 10.1016/j.ress.2025.111483
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    References listed on IDEAS

    as
    1. Feng, Jian Rui & Zhao, Meng-ke & Lu, Shou-xiang, 2024. "Accident spread and risk propagation mechanism in complex industrial system network," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    2. Arunthavanathan, Rajeevan & Khan, Faisal & Sajid, Zaman & Amin, Md. Tanjin & Kota, Kalyan Raj & Kumar, Shreyas, 2025. "Are the processing facilities safe and secured against cyber threats?," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    3. Tang, Daogui & Fang, Yi-Ping & Zio, Enrico, 2023. "Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    4. Peng, Xiangzhen & Zheng, Chengliang & Wang, Yidi & Cui, Xiaohui & Shen, Zhidong, 2025. "Double layer blockchain-assisted trusted data flow model for industrial control systems," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    5. Zhao, Hao & Pan, Rong, 2025. "Gaussian Derivative Change-point Detection for early warnings of industrial system failures," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    6. Yuan, Shuaiqi & Reniers, Genserik & Yang, Ming, 2024. "Integrated management of safety and security barriers in chemical plants to cope with emerging cyber-physical attack risks under uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    7. Daogui Tang & Yi-Ping Fang & Enrico Zio, 2023. "Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods," Post-Print hal-04103525, HAL.
    Full references (including those not matched with items on IDEAS)

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